Mapping genetic interactions (GIs) by simultaneously perturbing pairs of genes is a powerful tool for understanding complex biological phenomena. While the bulk of genetic interaction data has previously been generated in simpler model organisms such as yeast and bacteria, we have recently developed an experimental platform for generating quantitative GI maps in mammalian cells using a combinatorial RNAi strategy. We propose to apply this strategy to genetically study the host factors mediating infectivity of the Human Immunodeficiency Virus (HIV). Previous RNAi screens studying the host factors mediating HIV infectivity have identified approximately 1,200 genes, or over 5% of human protein coding genes. Only a handful of these putative HIV host factors have been fully characterized, and it is likely that many are false positives. We propose an alternative screening approach for studying HIV host factors, utilizing published biochemical and genetic screening data to inform a quantitative genetic interaction study. Our analysis will employ HIV infectivity, proliferation and cell morphology to produce several genetic interaction maps, or E-MAPs (epistasis maps). Through deep genetic interrogation of putative HIV host factors, this approach will yield an improved genetic analysis, clarifying previous biochemical and genetic data. The genetic interaction map will also provide information regarding the functional context of uncharacterized HIV host factors within cellular processes. Finally, we will validate novel host factors and pathways through functional studies in CD4+ T-cells, and investigate the context of verified HIV host factors within the HIV interactome and lifecycle.